ROHIT LAL

Person Follower

Abstract

Helper robots are widely used in various situations, for ex-ample at airports and railway stations. This paper presents a pipelineto multiplex the tracking and detection of a person in dynamic envi-ronments using a stereo camera in real-time. Recent developments inobject detection using ConvNets have led to robust person detection.These deep convolutional neural networks generally fail to run with highframes rates on devices with less computing power. Trackers are alsoused to retain the identity of the target person as well as imposefewerconstraints on hardware. A concept of multiplexed detection and tracking is used which makes the pipeline faster by many folds. TurtleBot-2is used for prototyping the robot and tuning of the motion controller.Robot Operating System (ROS) is used to set up communication be-tween various nodes of the pipeline. The results found were comparableto current state-of-the-art person followers and can be readily usedinday to day life.

Cyber-Physical Architecture

Number Plate Detection

Solution Overview

Our current solution (implemented) provides a robust registration plate detection, and extracts other features like car model, speed, face (if visible), date and time of entry/exit and upload the extracted data to a centralized IoT integrated database. Beneficiaries include malls, colleges, parking lots, etc. with multiple gates. Whenever the gate camera detects a departing car, the corresponding owner gets notified. Further, the owner can use the Alert feature to warn the guard. The web application has two levels of access, the first providing general information about a specific car to the corresponding owner, and the latter one for the Authority, which stores all the data of a campus. This can be used to monitor the traffic on the campus and for surveillance applications.

Cyber-Physical Architecture

Self Balancing Platform

Abstract

Control system is designed to stabilise the camera gimbal system used in different airborne systems for applications such as target tracking, surveillance, aerial photography, autonomous navigation and so on. The technique is applied in everything from self-stabilising cameras to helicopters and noise reducing equipment. This camera gimbal system replaces many traditional tracking systems such as radar which are heavy and large to mount on air vehicles. So, the stabilisation of camera gimbal is very important to eliminate shakes and vibrations in photography, provides accuracy.
NOTE: This project was selected for SIH-20 from our internal hackathon conducted by college. Further details will be shared after results of SIH-20

Circuit Diagram

Taxi v3 OpenAi Gym

Abstract

There are four designated locations in the grid world indicated by R(ed), G(reen), Y(ellow), and B(lue). When the episode starts, the taxi starts off at a random square and the passenger is at a random location. The taxi drives to the passenger's location, picks up the passenger, drives to the passenger's destination (another one of the four specified locations), and then drops off the passenger. Once the passenger is dropped off, the episode ends. Observations: There are 500 discrete states since there are 25 taxi positions, 5 possible locations of the passenger (including the case when the passenger is in the taxi), and 4 destination locations.This problem was solved using Q-Learning Approach. The model trained is consistently among top-5 in OpenAI Gym Leaderboard

Hand Gesture Robot

Abstract

The hand gesture controlled bot is a bot which receives it commands by giving pitch and roll to hand. This is helpful for people on wheelchair who can't even move their fingers or hands.These bots are very useful in many applications like remote surveillance, military etc. Hand gesture controlled robot can be used by physically challenged people for wheelchair control .Hand gesture controlled industrial grade robotic arms can be developed.

Circuit Diagram

Classifier from Scratch

Abstract

The code is written from scratch using pytorch for dataloading, matrix calculations and GPU acceleration. This was my first introduction to DL where I wrote the code myself along with learning various mathematics and techniques required to optimize a netowrk (PS. This also included learning ways to tune hyperparameters). Deep Learning Models Implemented are enlisted below:

• Logistic Regression (Not technically a deep learning model, but gives a base for Neural Networks)
• Deep Neural Network (Fully-connected layers only)

• Batch Gradient Descent
• Mini-batch Gradient Descent
• Stochastic Gradient Descent (put batch_size = 1 in mini-batch to get this)
• Batch Gradient Descent with Momentum
• Batch RMSProp
• Batch Adam